Analysis of convergence deformation remediation of shield tunnels by lateral grouting
Bibliographic record
Abstract
Grouting is recognized as an effective method for remediating convergence deformation in shield tunnels. However, simple and effective theoretical calculation methods to guide on-site construction are still lacking. By constructing a mechanical analysis model of tunnel deformation induced by horizontal lateral grouting, this study derives a mathematical expression for tunnel longitudinal convergence deformation caused by single-hole grouting. This analysis is further extended to cases involving double-hole and continuous multi-hole grouting on the same side. The theoretical method is validated by field monitoring data and numerical simulation, confirming its rationality. Under grouting pressure, the tunnel's transverse convergence deformation displays a “π”-shaped distribution along the longitudinal axis. This deformation shows a negative correlation with tunnel-to-grouting hole spacing and burial depth, and a positive correlation with grouting pressure. Tunnel stiffness and soil cohesion have minimal impact on the convergence deformation. The research provides a reference for predicting tunnel convergence deformation resulting from grouting activities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".